Flourishing by Design: Applying Self-Determination Theory and the Job Demands-Resources Model to Systems-Level Wellness in Medical Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Physician burnout remains a defining challenge in medical education, driven by excessive demands and fragmented wellness initiatives. While calls for systemic reform grow louder, many efforts lack a unifying framework capable of addressing both distress and the cultivation of professional fulfillment. Methods: This guide applies a dual-theory lens-Self-Determination Theory (SDT) and the Job Demands-Resources (JD-R) model-to propose a systems-based approach to motivation and wellness. Drawing on empirical evidence and applied experience, it presents twelve actionable strategies across three ecological domains: the built environment, policy frameworks, and interpersonal dynamics. The first six strategies target hindrance demands that frustrate psychological needs and contribute to burnout; the next six strengthen resources that satisfy those needs and foster engagement, resilience, and well-being. Results: The strategies offer flexible, theoretically grounded entry points for reform, supporting institutions in cultivating sustainable, human-centered learning environments where wellness is embedded-not bolted on. Examples include prioritizing formative over high-stakes assessments, integrating justice and safety into institutional design, and balancing clinical responsibility with developmental support. Conclusions: Integrating SDT and JD-R provides a rigorous, coherent, and scalable foundation for systems-level wellness initiatives. It reframes well-being not as the absence of burnout but as the presence of flourishing-offering a shared language, validated metrics, and a roadmap for lasting cultural and structural transformation in medical education.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it